The system
operation (maintenance) is a stochastic process based upon the equipment, their
maintenance, their preparation, and also based upon the personnel carrying out
repair, and upon the regulations. This process, which is in fact the complex of
events that happen to the system, or to one of its subsystems, or its equipment
(that is to the object of operation) from its manufacturing to its discarding,
is a random in time and frequency succession of states of operation. From
mathematical point of view, technical systems’ maintenance is a discrete state
space stochastic process without after-effects so it can be approximated with a
Markov-chain.

Aims of this research area are
to discuss mathematical modeling and simulation of operation
processes and to investigate their possibilities of use for maintenance
management decision making.

Application of Fuzzy Methods for Decision Making of Technical Management

Fuzzy set theory is a
relatively new mathematical tool to depict and model inaccuracy and uncertainty
of the real world and human thinking.

Nowadays it is indispensable to investigate and to develop
new methods in technical management because of this area has had growth a lot.
The researched area of our Virtual Lab of Process & System Modeling
is focusing on fuzzy set theory-, and on fuzzy logic based

The main application of mathematics in the engineering is
the mathematical modeling. Using mathematical models we should solve different
tasks of system analysis and synthesis. During mathematical modeling
engineers can meet any type and rate model and system uncertainty. Its reasons
can be incognizance of modelers, data inaccuracy or any technical (e.g.
technological, environmental) problem.

Our aims are to discuss types of mathematical modeling
and simulation uncertainties furthermore to investigate methods to get used to
analyze them.

Modeling for evaluation of organizational and technical readiness in implementing Business Intelligence projects

Main
objective of each company is to serve its customers and the ability
to track,
understand, and manage information within the company is very
important in operating and providing good service. Business
intelligence (BI) technology gives this ability to the managers and
experts of companies. But nowadays BI systems include one of
the largest and fastest growing areas of IT expenditure in companies
and if the BI project fail, they will lose a lot of money.

For
reducing costs through BI implementation and preventing from fail of
BI project, we need to evaluate readiness of companies from two
aspects: Organizational and Technical.

The
main objective of working on this research area is to make a model
for evaluating companies’ readiness for implementing BI projects.
This model will enable us to assay and evaluate readiness of
companies from technical and organizational aspects.